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      Comparing viral metagenomics methods using a highly multiplexed human viral pathogens reagent

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          Highlights

          • Metagenomics can detect any known viruses in clinical samples.

          • We compared different viral metagenomic library preparation methods using a biological reagent consisting of 25 human viral pathogens.

          • Our study will assist in the development of efficient applications of viral metagenomics.

          Abstract

          Unbiased metagenomic sequencing holds significant potential as a diagnostic tool for the simultaneous detection of any previously genetically described viral nucleic acids in clinical samples. Viral genome sequences can also inform on likely phenotypes including drug susceptibility or neutralization serotypes. In this study, different variables of the laboratory methods often used to generate viral metagenomics libraries were compared for their abilities to detect multiple viruses and generate full genome coverage. A biological reagent consisting of 25 different human RNA and DNA viral pathogens was used to estimate the effect of filtration and nuclease digestion, DNA/RNA extraction methods, pre-amplification and the use of different library preparation kits on the detection of viral nucleic acids. Filtration and nuclease treatment led to slight decreases in the percentage of viral sequence reads and number of viruses detected. For nucleic acid extractions silica spin columns improved viral sequence recovery relative to magnetic beads and Trizol extraction. Pre-amplification using random RT-PCR while generating more viral sequence reads resulted in detection of fewer viruses, more overlapping sequences, and lower genome coverage. The ScriptSeq library preparation method retrieved more viruses and a greater fraction of their genomes than the TruSeq and Nextera methods. Viral metagenomics sequencing was able to simultaneously detect up to 22 different viruses in the biological reagent analyzed including all those detected by qPCR. Further optimization will be required for the detection of viruses in biologically more complex samples such as tissues, blood, or feces.

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          Most cited references29

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          Cloning of a human parvovirus by molecular screening of respiratory tract samples.

          The identification of new virus species is a key issue for the study of infectious disease but is technically very difficult. We developed a system for large-scale molecular virus screening of clinical samples based on host DNA depletion, random PCR amplification, large-scale sequencing, and bioinformatics. The technology was applied to pooled human respiratory tract samples. The first experiments detected seven human virus species without the use of any specific reagent. Among the detected viruses were one coronavirus and one parvovirus, both of which were at that time uncharacterized. The parvovirus, provisionally named human bocavirus, was in a retrospective clinical study detected in 17 additional patients and associated with lower respiratory tract infections in children. The molecular virus screening procedure provides a general culture-independent solution to the problem of detecting unknown virus species in single or pooled samples. We suggest that a systematic exploration of the viruses that infect humans, "the human virome," can be initiated.
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            Performance comparison of benchtop high-throughput sequencing platforms.

            Three benchtop high-throughput sequencing instruments are now available. The 454 GS Junior (Roche), MiSeq (Illumina) and Ion Torrent PGM (Life Technologies) are laser-printer sized and offer modest set-up and running costs. Each instrument can generate data required for a draft bacterial genome sequence in days, making them attractive for identifying and characterizing pathogens in the clinical setting. We compared the performance of these instruments by sequencing an isolate of Escherichia coli O104:H4, which caused an outbreak of food poisoning in Germany in 2011. The MiSeq had the highest throughput per run (1.6 Gb/run, 60 Mb/h) and lowest error rates. The 454 GS Junior generated the longest reads (up to 600 bases) and most contiguous assemblies but had the lowest throughput (70 Mb/run, 9 Mb/h). Run in 100-bp mode, the Ion Torrent PGM had the highest throughput (80–100 Mb/h). Unlike the MiSeq, the Ion Torrent PGM and 454 GS Junior both produced homopolymer-associated indel errors (1.5 and 0.38 errors per 100 bases, respectively).
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              Is Open Access

              MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads

              An important step in ‘metagenomics’ analysis is the assembly of multiple genomes from mixed sequence reads of multiple species in a microbial community. Most conventional pipelines use a single-genome assembler with carefully optimized parameters. A limitation of a single-genome assembler for de novo metagenome assembly is that sequences of highly abundant species are likely misidentified as repeats in a single genome, resulting in a number of small fragmented scaffolds. We extended a single-genome assembler for short reads, known as ‘Velvet’, to metagenome assembly, which we called ‘MetaVelvet’, for mixed short reads of multiple species. Our fundamental concept was to first decompose a de Bruijn graph constructed from mixed short reads into individual sub-graphs, and second, to build scaffolds based on each decomposed de Bruijn sub-graph as an isolate species genome. We made use of two features, the coverage (abundance) difference and graph connectivity, for the decomposition of the de Bruijn graph. For simulated datasets, MetaVelvet succeeded in generating significantly higher N50 scores than any single-genome assemblers. MetaVelvet also reconstructed relatively low-coverage genome sequences as scaffolds. On real datasets of human gut microbial read data, MetaVelvet produced longer scaffolds and increased the number of predicted genes.
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                Author and article information

                Contributors
                Journal
                J Virol Methods
                J. Virol. Methods
                Journal of Virological Methods
                Elsevier B.V.
                0166-0934
                1879-0984
                11 December 2014
                1 March 2015
                11 December 2014
                : 213
                : 139-146
                Affiliations
                [a ]Blood Systems Research Institute, San Francisco, CA, USA
                [b ]Department of Laboratory Medicine, University of California, San Francisco, CA, USA
                [c ]Division of Virology, National Institute for Biological Reagents and Control, Medicines and Healthcare Products Regulatory Agency, Hertfordshire, UK
                Author notes
                [* ]Corresponding author at: Blood Systems Research Institute, 270 Masonic Ave., San Francisco, CA 94118, USA. Tel.: +1 415 923 5763; fax: +1 415 567 5899. delwarte@ 123456medicine.ucsf.edu edelwart@ 123456bloodsystems.org
                Article
                S0166-0934(14)00461-3
                10.1016/j.jviromet.2014.12.002
                4344864
                25497414
                810d75ea-996d-4e07-9970-6f62ce689220
                Copyright © 2014 Elsevier B.V. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 29 September 2014
                : 26 November 2014
                : 3 December 2014
                Categories
                Article

                Microbiology & Virology
                viral metagenomics,next generation sequencing,virus pathogen discovery,diagnosis,method

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